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新疆乌什县核桃优树坚果性状评价 被引量:20

Evaluation on Walnut Nut Characters of Superior Tree in Xinjiang Wushi County
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摘要 【目的】对新疆乌什县核桃优树的果实进行评价,为新疆核桃选优及优树评价建立科学的评价体系奠定基础,为今后核桃产业发展及林果产业储备优良种质做准备。【方法】通过对新疆乌什县1970年前后选出的18株核桃优树的表观性状进行评分,并对其5种主要经济性状(三径平均、单果重、坚果壳厚、坚果出仁率、核仁重)进行主成分分析,依性状累积方差贡献率达到85%以上,提出了两个反映核桃主要经济性状的主成分及其主成分函数式。通过计算各优树的重要主成分,结合表观性状的评分,进而选择综合经济性状优良的品种。【结果】根据主成分分析及核桃果实表观性状的评分,最终表明4号核桃优树的果实综合指标最佳。【结论】应用主成分法并结合综合评分建立核桃优树果实评价体系,在生产中具有重要应用价值。 [ Objective ] This study will lay the foundation for establishing scientific evaluation system for Xinjiang walnut optimum choice and evaluating nuts of excellent walnuts and preparing fine germplasm reserves for future walnut industrial development. [ Method ] The apparent traits rating of 18 strains walnut quality saplings were graded which were elected from Wusih county , Xinjiang in 1970, its five kinds of main economic characters were andlyzed (three diameter average, single fruit weight, nut shell thickness, kernel rate, kernel weight) by principal component. According to characters cumulated variance, the contribution rate reaches above 85%, two principal components and its principal component functional equation of reflected walnut main economic characters were verified. The important principal components of all the superior walnut trees were calculated and were graded by apparent traits then to choose the superior walnut varieties with fine comprehensive economic traits. [ Result] According to principal component analysis and grading of walnut fruit characters, it was shown that the walnut quality saplings 4 had the best fruit comprehensive index. [ Conclusion] The evaluation system about fruit of walnut superior trees was established by principal component method and comprehensive pointrating, which had important application value in the production process.
出处 《新疆农业科学》 CAS CSCD 北大核心 2011年第1期53-59,共7页 Xinjiang Agricultural Sciences
基金 国家自然科学基金项目(30860230) "十一五"国家科技支撑计划课题(2007BAD36B03-1) 2010年新疆财政林业科技专项资金
关键词 核桃优树 果实 性状评价 主成分分析 walnut superior trees fruit character evaluation principal component analysis
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